The whole energy market, from production plants to end-users, is marked by a strong impulse towards a sustainable use of raw materials and resources, and a reduction of its carbon foot-print. Increasing the split of energy produced with renewables, improving the efficiency of the power plants and reducing the waste of energy appear to be mandatory steps to reach the goal of sustainability. The steam turbines are present in the power generation market with different roles: they are used in fossil, combined cycles, geothermal and concentrated solar plants, but also in waste-to-energy and heat recovery applications. Therefore, they still play a primary role in the energy production market. There are many chances for efficiency improvement in steam turbines, and from a rational point of view, it is important to consider that the LP section contributes to the overall power delivered by the turbine typically by around 40% in industrial power generation. Therefore, the industry is more than ever interested in developing methodologies capable of providing a reliable estimate of the LP stages efficiency, while reducing development costs and time. This paper presents the results obtained using a CFD commercial code with a set of user defined subroutines to model the effects of non-equilibrium steam evolution, droplets nucleation and growth. The numerical results have been compared to well-known test cases available in literature, to show the effects of different modeling hypotheses. The paper then focuses on a test case relevant to a cascade configuration, to show the code capability in terms of bladerow efficiency prediction. Finally, a comprehensive view of the obtained results is done through comparison with existing correlations.
Two Phase Flow CFD Modeling to Enhance Steam Turbines LP Stages Performance Predictability: Comparison With Data and Correlations / Nicola Maceli, Lorenzo Arcangeli, Andrea Arnone. - ELETTRONICO. - 9: Oil and Gas Applications; Organic Rankine Cycle Power Systems; Steam Turbine:(2020), pp. 0-0. (Intervento presentato al convegno ASME Turbo Expo 2020 Turbomachinery Technical Conference and Exposition tenutosi a Virtual Event nel September 21 - 25, 2020) [10.1115/GT2020-16312].
Two Phase Flow CFD Modeling to Enhance Steam Turbines LP Stages Performance Predictability: Comparison With Data and Correlations.
Nicola Maceli;Andrea Arnone
2020
Abstract
The whole energy market, from production plants to end-users, is marked by a strong impulse towards a sustainable use of raw materials and resources, and a reduction of its carbon foot-print. Increasing the split of energy produced with renewables, improving the efficiency of the power plants and reducing the waste of energy appear to be mandatory steps to reach the goal of sustainability. The steam turbines are present in the power generation market with different roles: they are used in fossil, combined cycles, geothermal and concentrated solar plants, but also in waste-to-energy and heat recovery applications. Therefore, they still play a primary role in the energy production market. There are many chances for efficiency improvement in steam turbines, and from a rational point of view, it is important to consider that the LP section contributes to the overall power delivered by the turbine typically by around 40% in industrial power generation. Therefore, the industry is more than ever interested in developing methodologies capable of providing a reliable estimate of the LP stages efficiency, while reducing development costs and time. This paper presents the results obtained using a CFD commercial code with a set of user defined subroutines to model the effects of non-equilibrium steam evolution, droplets nucleation and growth. The numerical results have been compared to well-known test cases available in literature, to show the effects of different modeling hypotheses. The paper then focuses on a test case relevant to a cascade configuration, to show the code capability in terms of bladerow efficiency prediction. Finally, a comprehensive view of the obtained results is done through comparison with existing correlations.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.